#socialmediadata

📢 Social Media & Influencer Dataset – Global

Influencer marketing is transforming the way brands connect with audiences, but success depends on #DataDrivenDecisions. Our #SocialMedia & #InfluencerDataset empowers businesses with:

✅ Comprehensive influencer profiles across Instagram, TikTok, Twitter, and Telegram

✅ Engagement metrics & follower analytics

✅ Campaign insights & ROI simulations

✅ Trending topics and campaign performance by region

With this #Dataset, #MarketingTeams, agencies, and platforms can optimize influencer collaborations, #BoostCampaign effectiveness, and #MaximizeROI.

At Actowiz Solutions, we provide accurate, #RealTimeDatasets that help brands move from guesswork to precision marketing.

🚀 Power your next influencer campaign with actionable insights!

1. audience data

2. SEO data

3. social media data can be accessed at the following Twitter thread.

There is nothing better on a Sunday morning than starting your day the lazy way: a slow roll out of bed without bothering to change into ‘day clothes’, a cup of coffee, and, for myself at least, a scroll through ‘my socials’ to begin building a picture of the day ahead. My Facebook feed is filled (if we pretend the relentless product advertising and viral posts don’t pop up) with sentimental birthday posts for family and friends, snapshots of holidays somewhere far sunnier than here, and comments that are only understood by those included in the inside joke.

Perhaps the politicians of Australia can provide a trustworthy resources for today’s topics of interest... and lo and behold, former Liberal politician Clive Palmer has delivered. A personal favourite of mine was the morning he shared a Star Wars meme, only the scene depicted was that of Greens party members screaming in fear at a self-help book ‘Economics for Dummies.’ As usual, this post was well received, with one social media user describing it as “another high-tier Palmer meme.” But Palmer’s social media activity poses the question of his level of genuine engagement with his audiences, and hence his interest in genuine connections. His position as former politician may cut him some slack, but the change in his social reputation, obvious by a quick Google search of his name and the resulting hundred of discussions of his hilarity, is sure to precede him. We know Palmer loves his memes, but do we know anything at all about Palmer on a personal level? Do we even have the right to expect this type of connection?

Author Greg Jericho suggests politicians and parties are “only able to overcome the... nature of social media when they forego the need to completely control the debate,” (2012, pp.302). That is, the risks involved in opening discussion in such a public arena are unavoidable if one wants to create real connections on social media platforms. Gone are the days of gatherings in the town square, where your comments may spread via hearsay and gossip for weeks to come. Now, our comments and opinions are forever embedded in data, to be analysed and picked apart by users irrespective of time and space. Whilst this social media data can serve as an invaluable resource for building a “profile of voters,” the flow of communication travels both ways, an affordance of social media that forces vulnerability on its users (Jericho, 2012, pp.308).

Social media is not only engaging as a means of direct communication, but also as a platform for news and current affairs dissemination. Activist Eli Pariser argues, however, that the effects of platform algorithms, such as the process by which a Google Search returns results to a user, can create what is known as a ‘filter bubble;’ an invisible internet bubble that shows users content it already knows the user is looking for or supports. The filter bubble theory rejects the idea of an unbiased Internet, however many users engage with social media as a tool for sourcing political information because of the perceived freedoms of platforms for information sharing.

Professor Gunn Enli uses data statistics to illustrate the influence of social media use when compared to traditional media use; during the 2016 presidential election campaign, Republican candidate Donald Trump (well known for his controversial tweets and posts) boasted 17.6 million Twitter followers, whilst The New York Times paled in comparison with their 1.2 million online subscribers (2017, pp.53). With Trump’s audience dominating that of the Times, it really is no surprise his campaign garnered a tremendous amount of both online support and loathing. I wonder if Clive Palmer will ever hit those kinds of numbers...

References

Enli, G 2017. ‘Twitter as an arena for the authentic outsider: Exploring the social media campaigns of Trump and Clinton in the 2016 presidential election,’ European Journal of Communication, 32:1.

This article brings up a good point to keep in mind about the limitations of big data.  "Data only tells you about the population and actions of individuals it represents, which inevitably excludes part of the population."  Though the examples of two individuals represent extreme opposites (the first being highly valuable to marketers), the point is about being aware of restricted data flows, which is pertinent to what I do everyday.   Let's say a client wants to expand their social reach to a new market demographic.  We have data on their current audience, but lack data on the target audience--the untracked populations.  We may consider ecosystem or competitive tracking around a topic or similar brands, or consult outside research.  

We have even less of an understanding of the populations whose behaviors occur offline.  For clients who aim to reach audiences that are less active online, the restriction of data flows from this population presents a major difficulty.  Mindfulness and careful planning are worthwhile investments to accomplish the brand goal and related business objectives.  

Not only do limitations include the lack of data on all populations, they also include lack of data for certain metrics.  For instance, age data collected through social listening tools often come from two sources: Facebook and YouTube.  We can make inferences about age segments of the population on these networks, but reaching them on other networks where age data is unattainable requires extrapolation.